[CLAUDE] Docs: setup RAG Framework v1.3 governance + eval framework

- docs/governance/README.md: Path B delegation stub → AI_INFRA canonical
  Phase/BC vocabulary documented (9 phase + 10 BC SOLUTION_ERP-specific)
- .claude/rag.json: add _decision_log block (10 rationale entries) +
  add .claude/agents/**/*.md to corpus_paths (fix Case D harvest gap)
- eval/evaluator.md: inline executor spec v1.0 (Spec A strict)
- eval/golden-set-solution_erp.jsonl: 14-entry golden set v1.1
  (5 gotcha + 3 pattern + 3 decision + 3 negative)
- eval/runs/2026-05-26-baseline-v1.0-failed.json: v1.0 attempt
  recall@5=0.455 FAIL — root cause diagnosis Case A/C/D
- eval/runs/2026-05-26-baseline-v1.1-pending.json: v1.1 attempt
  pending CLI restart for accurate numbers
- eval/trial-state-lock.json: 2-section split (quality_gate +
  drift_monitor) per v1.3 §6.2, 4-week milestones 2026-05-26 → 2026-06-23

CRITICAL lesson: bootstrap.py --project flag overrides collection name only.
Use --config D:\...\SOLUTION_ERP\.claude\rag.json for correct project root.
Old projects.json had root_path=AI_INFRA for solution_erp (Anti #24) — FIXED.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

eval/evaluator.md

@@ -0,0 +1,95 @@
+# Eval Executor Spec — SOLUTION_ERP
+
+> **Version:** v1.0 (2026-05-26)
+> **Spec:** A — Strict (expected chunk must appear in top-5, rerank ≥ 0.7 = confident hit)
+> **Framework:** RAG v1.3 §6.3 — Spec A vs B locked BEFORE first baseline
+> **Companion:** `RAG-FRAMEWORK-V1.3-SETUP-GUIDE.md` §6
+
+---
+
+## Execution protocol
+
+### 1. Run search_memory for each query
+
+```python
+# Fire all 14 queries in parallel (MCP tool)
+mcp__rag-unified__search_memory(
+    query=<query>,
+    scope="self",      # project = solution_erp
+    top_k=5,
+    use_rerank=True
+)
+```
+
+### 2. Scoring per query (Spec A — Strict)
+
+| Hit condition | Score |
+|---|---|
+| Expected source_path appears in top-5 AND rerank ≥ 0.7 | ✅ HIT |
+| Expected source_path appears in top-5 BUT rerank < 0.7 | ✗ MISS (Case A suspect) |
+| Expected source_path NOT in top-5 | ✗ MISS — classify Case B/C/D |
+| Negative query: 0 results OR all rerank < 0.7 | ✅ CORRECT EXCLUSION |
+
+### 3. recall@5 calculation
+
+```
+recall@5 = hits / positive_queries
+positive_queries = 11 (q01-q11, excluding 3 negative q12-q14)
+gate_threshold = 0.7 → must hit ≥ 8/11
+```
+
+### 4. Case classification for failures
+
+Per v1.3 §10:
+- **Case A:** chunk in top-5 but rerank low → threshold calibration
+- **Case B:** chunk NOT top-5 but IS top-20 → retrieval param tuning
+- **Case C:** chunk NOT top-20 but verbatim phrase IS in corpus → rerank context-density bias
+- **Case D:** verbatim phrase NOT in corpus → harvest gap
+
+### 5. Output format
+
+Save to `eval/runs/YYYY-MM-DD-baseline-vN.N.json`:
+
+```json
+{
+  "run_date": "YYYY-MM-DD",
+  "golden_set_version": "vN.N",
+  "spec": "A",
+  "results": [
+    {
+      "id": "q01",
+      "query": "...",
+      "expected_source": "...",
+      "hit": true/false,
+      "top_1_source": "...",
+      "top_1_rerank": 0.000,
+      "case": null/"A"/"B"/"C"/"D"
+    }
+  ],
+  "recall_at_5": 0.000,
+  "avg_top1_rerank": 0.000,
+  "pass_gate": true/false
+}
+```
+
+---
+
+## Golden set file
+
+`eval/golden-set-solution_erp.jsonl` — 14 entries (immutable during trial period)
+
+**Mutation rules:**
+- ❌ DO NOT rephrase query mid-trial (Anti #11)
+- ❌ DO NOT modify expected_source_paths post-baseline (Anti #12)
+- ✅ Version bump v1.0 → v1.1 OK WITH lock of prior version + transparent re-author (AI_INFRA lesson §3.5)
+
+---
+
+## Weekly Friday execution
+
+1. Fire 14 queries SAME (no modification)
+2. Score → recall@5 + avg_rerank
+3. Compare vs `eval/trial-state-lock.json` baseline
+4. Check chunk_count drift (Qdrant LIVE vs baseline)
+5. Update lock file milestone status
+6. If recall < gate → apply §15.1 4-cause triage